Detection of Maize Kernels Breakage Rate Based on K-means Clustering
文献类型：会议论文
| 作者 | Gao L(高雷) ; Wang Z(王卓); Yang L(杨亮); Bai XP(白晓平)
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| 出版日期 | 2017 |
| 会议名称 | 5th International Conference on Computer-Aided Design, Manufacturing, Modeling and Simulation (CDMMS) |
| 会议日期 | April 22-23, 2017 |
| 会议地点 | Busan, SOUTH KOREA |
| 关键词 | Computer vision K-means clustering detection of the maize kernels breakage energy function of gradient image clarity evaluation |
| 页码 | 1-6 |
| 通讯作者 | Yang L(杨亮) |
| 中文摘要 | In order to optimize the recognition accuracy of maize kernels breakage detection and improve the detection efficiency of maize kernels breakage, this paper using computer vision technology and detecting of the maize kernels breakage based on K-means clustering algorithm. First, the collected RGB images are converted into Lab images, then the original images clarity evaluation are evaluated by the energy function of Sobel 8 gradient. Finally, the detection of maize kernels breakage using different pixel acquisition equipments and different shooting angles. In this paper, the broken maize kernels are identified by the color difference between integrity kernels and broken kernels. The original images clarity evaluation and different shooting angles are taken to verify that the clarity and shooting angles of the images have a direct influence on the feature extraction. The results show that K-means clustering algorithm can distinguish the broken maize kernels effectively. |
| 收录类别 | CPCI（ISTP） |
| 产权排序 | 1 |
| 会议录 | 2017 5TH INTERNATIONAL CONFERENCE ON COMPUTER-AIDED DESIGN, MANUFACTURING, MODELING AND SIMULATION (CDMMS 2017)
 |
| 会议录出版者 | AMER INST PHYSICS |
| 会议录出版地 | MELVILLE |
| 语种 | 英语 |
| ISSN号 | 0094-243X |
| ISBN号 | 978-0-7354-1504-1 |
| WOS记录号 | WOS:000405777700051 |
| 源URL | [http://ir.sia.cn/handle/173321/20824]  |
| 专题 | 沈阳自动化研究所_数字工厂研究室 |
| 作者单位 | 1.Key Laboratory of Networked Control System, Chinese Academy of Sciences, Shenyang 110016, China 2.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 3.University of Chinese Academy of Sciences, Beijing 100049, China |
| 推荐引用方式 GB/T 7714 | Gao L,Wang Z,Yang L,et al. Detection of Maize Kernels Breakage Rate Based on K-means Clustering[C]. 见:5th International Conference on Computer-Aided Design, Manufacturing, Modeling and Simulation (CDMMS). Busan, SOUTH KOREA. April 22-23, 2017. |
入库方式： OAI收割
来源：沈阳自动化研究所
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